Correlation Between Rongsheng Petrochemical and Lier Chemical
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By analyzing existing cross correlation between Rongsheng Petrochemical Co and Lier Chemical Co, you can compare the effects of market volatilities on Rongsheng Petrochemical and Lier Chemical and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Rongsheng Petrochemical with a short position of Lier Chemical. Check out your portfolio center. Please also check ongoing floating volatility patterns of Rongsheng Petrochemical and Lier Chemical.
Diversification Opportunities for Rongsheng Petrochemical and Lier Chemical
0.66 | Correlation Coefficient |
Poor diversification
The 3 months correlation between Rongsheng and Lier is 0.66. Overlapping area represents the amount of risk that can be diversified away by holding Rongsheng Petrochemical Co and Lier Chemical Co in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Lier Chemical and Rongsheng Petrochemical is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Rongsheng Petrochemical Co are associated (or correlated) with Lier Chemical. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Lier Chemical has no effect on the direction of Rongsheng Petrochemical i.e., Rongsheng Petrochemical and Lier Chemical go up and down completely randomly.
Pair Corralation between Rongsheng Petrochemical and Lier Chemical
Assuming the 90 days trading horizon Rongsheng Petrochemical Co is expected to under-perform the Lier Chemical. But the stock apears to be less risky and, when comparing its historical volatility, Rongsheng Petrochemical Co is 1.08 times less risky than Lier Chemical. The stock trades about -0.25 of its potential returns per unit of risk. The Lier Chemical Co is currently generating about 0.02 of returns per unit of risk over similar time horizon. If you would invest 841.00 in Lier Chemical Co on October 25, 2024 and sell it today you would earn a total of 3.00 from holding Lier Chemical Co or generate 0.36% return on investment over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Significant |
| Accuracy | 100.0% |
| Values | Daily Returns |
Rongsheng Petrochemical Co vs. Lier Chemical Co
Performance |
| Timeline |
| Rongsheng Petrochemical |
| Lier Chemical |
Rongsheng Petrochemical and Lier Chemical Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Rongsheng Petrochemical and Lier Chemical
The main advantage of trading using opposite Rongsheng Petrochemical and Lier Chemical positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Rongsheng Petrochemical position performs unexpectedly, Lier Chemical can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Lier Chemical will offset losses from the drop in Lier Chemical's long position.The idea behind Rongsheng Petrochemical Co and Lier Chemical Co pairs trading is to make the combined position market-neutral, meaning the overall market's direction will not affect its win or loss (or potential downside or upside). This can be achieved by designing a pairs trade with two highly correlated stocks or equities that operate in a similar space or sector, making it possible to obtain profits through simple and relatively low-risk investment.
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Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Equity Forecasting module to use basic forecasting models to generate price predictions and determine price momentum.
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